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DYNAMICE: An integrated framework for biomechanical phenotyping of arteries to disentangle mechanical causes of arterial stiffening in diabetes

Periodic Reporting for period 1 - DYNAMICE (DYNAMICE: An integrated framework for biomechanical phenotyping of arteries to disentangle mechanical causes of arterial stiffening in diabetes)

Reporting period: 2019-04-01 to 2021-03-31

Accelerated arterial stiffening, an important complication in diabetes, increases cardiac workload eventually leading to heart failure. The arterial wall —consisting of elastin, collagen, smooth muscle, and glycosaminoglycans— may stiffen in diabetes due to 1) advanced glycation end-product (AGE)-induced collagen cross-linking, 2) calcification, or 3) changed glycosaminoglycan composition. The exact mechanical stiffening effects of these processes are unknown. Current preclinical, state-of-the-art measurement methods characterise arterial wall mechanics under static conditions. However, AGE-induced and glycosaminoglycan-associated wall stiffening may particularly affect dynamic characteristics (viscoelasticity) — especially relevant in vivo where arteries are subject to pulsatile blood pressure. The novel set-up for mechanical characterisation under such dynamic conditions I have previously developed still requires a matching computer modelling framework to correctly interpret the multidimensional, dynamic measurement data. I aim to 1) develop this modelling framework and 2) use it to quantify the characteristics of diabetes-associated stiffening processes by studying murine arteries with increased calcification, collagen cross-linking, glycosaminoglycan content, and combinations thereof. The forthcoming measurement platform —already sparking interest internationally— enables realistic preclinical biomechanical arterial characterisation and will be the integrative keystone in arterial stiffness research. Its application to diabetes-associated arterial stiffening may yield breakthrough target and focus to further treatment of patients.

Being a Marie Curie Global Fellowship, this fellowship consists of two periods: 1) an outgoing phase at Yale University (United States), and 2) a return-to-the-EU phase at Maastricht University (the Netherlands). This report pertains to period #1, as period #2 is still in progress.
At Yale University, we studied biaxial arterial biomechanics using the current state-of-the-art methodology. This has led to several novel findings. First, we discovered a key role of the genetic background in arterial remodelling with hypertension. Second, further studying this, we found strong evidence that this role of genetic background is through differences in arterial contractility, modulating the arterial inflammatory response. Third, in a related project, we showed that when ageing and hypertension are combined in murine models, ageing has a more pronounced effect than hypertension on arterial stiffening.

While working on these projects, we implemented from scratch a thick-walled, bi-layered model of arterial wall mechanics, including an explicit model of active smooth muscle contraction. This was extended into a growth and remodelling formulation, where such smooth muscle contraction modulates arterial tone and in turn influences arterial remodelling and inflammation.

In parallel, through collaboration with Maastricht University, we studied the effects of the diabetes-related crosslinking effects of methylglyoxal (MGO), one of the most potent AGE precursors, in multiple studies. First, we performed a literature review and found that in the current literature, there is no direct evidence to date of an association between MGO or MGO-derived advanced glycation end-products, and arterial stiffening. Second, in a preclinical study, we investigated how oral MGO supplementation influenced arterial stiffness. Third, we tested how direct incubation of an artery in a high-concentration MGO solution alters its mechanics. Fourth, in a clinical cross-sectional cohort study, we assessed whether there was an association between plasma MGO concentration and arterial stiffness. Finally, in a clinical study, we assessed whether pyridoxamine, an AGE inhibitor, attenuated arterial stiffening. We did not observe such effect.

At Maastricht University, we also preclinically studied the effects of arterial calcification on arterial stiffness by comparing groups subjected to different durations of warfarin treatment (inducing calcification). We are currently working on modelling these results. Finally, we developed a methodology to reliably quantify the vascular smooth muscle cell density in the arterial wall, based on two-photon laser scanning microscopy.
The novel bi-axial testing setup details (also see attached figure) have been published and its reproducibility thoroughly assessed. In the meantime, this methodology has generated international interest, and already multiple ongoing studies utilise this technology. The use of this technology to assess arterial disease will firmly advance our understanding of arterial biomechanics under realistic, in vivo-like conditions. Note that, although this project per se is focused on diabetes, the developed pulsatile biaxial testing methodology is universally applicable to study other arterial pathologies, including e.g. hypertensive arterial remodelling, vasculitis (including COVID 19-related), fibromuscular dysplasia, etc.

The knowledge gained from in vitro biomechanical experimentation can also be used for better patient diagnosis using in vivo biomechanical measurements. By using the same, consistent methodology to study biomechanical phenotypes in many preclinical models, we will build a ‘dictionary’ or ‘atlas’ of biomechanical disease signatures. Such a dictionary can subsequently be used to ‘look up’ in vivo biomechanics data and potentially diagnose disease. This approach reinforces the importance of our pulsatile way of measurement: by capturing and characterising biomechanics under in vivo-like conditions, the resulting data can be directly used as a comparator for (true) in vivo data.
Novel pulsatile bi-axial testing setup